Resolving Harvesting Errors in Institutional Repository Migration : Using Python Scripts with VS Code and LLM Integration. by satoshi hashimoto(橋本 郷史) (18851272)

“…Therefore, we decided to create a dedicated Python program using Large Language Model (LLM)-assisted coding.…”

An example of how segmentation corrects tracking during execution. by Khelina Fedorchuk (19130089)

Segmentation module training details. by Khelina Fedorchuk (19130089)

Comparison of MODIS and SGLI Albedo Retrievals Over the Sea of Okhotsk (January-May 2021) by Yingzhen Zhou (19723405)

“…Values are provided for the period January-May 2021 on a grid with a spatial resolution of 1 km.…”

A list of all facial muscle movements mentioned in the chimpFACS manual [5] and considered in our present study. by Aisha Mahmoud (20623732)

A list of all facial muscle movements mentioned in the catFACS manual [14] and considered in our present study. by Aisha Mahmoud (20623732)

Modules organization over different course editions. by Gabriele Pozzati (21094166)

Model fitting to neighborhood-level COVID-19 case data. by Renquan Zhang (13167533)

Summary of Tourism Dataset. by Jing Zhang (23775)

“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”

Segment-wise Spending Analysis. by Jing Zhang (23775)

“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”

Hyperparameter Parameter Setting. by Jing Zhang (23775)

“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”

Marketing Campaign Analysis. by Jing Zhang (23775)

“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”

Visitor Segmentation Validation Accuracy. by Jing Zhang (23775)

“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”

Integration of VAE and RNN Architecture. by Jing Zhang (23775)

“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”

<b>Challenges and Strategies for the Management of Quality-Oriented Education Bases in Universities under Informatization Background</b> by Yang Yanxi (21571568)

“…<p dir="ltr">The “CapabilityLayerInterviewData” set documents a coding-level snapshot of 24 semi-structured interviews conducted with practice-base managers at six Chinese universities between March and May 2024. Audio was captured on a Sony ICD-UX570 recorder, transcribed with iFlytek-SR (v3.1) at a word-error rate of ≈5 %, and imported into NVivo 14 for thematic coding. …”

MCCN Case Study 3 - Select optimal survey locality by Donald Hobern (21435904)

“…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”

Environmental Census: Modeling Synthetic Biology Ecological Risk with Metagenomic Enzymatic Data and High-Performance Computing by John Docter (22772100)

“…As the synthetic biology market develops and deploys new technologies, these engineered organisms may escape into unintended environments. Improved predictive computational tools are necessary to assess the potential establishment risk and environmental location of these escaped engineered microorganisms, assisting their design and management. …”

Exploring post-wildfire hydrologic response in central Colorado using field observations and the Landlab modeling framework by Jordan Adams (595056)

“…<p dir="ltr">In May 1996, the Buffalo Creek fire burned nearly 5,000 hectares of National Forest and private land 60 miles southwest of Denver, Colorado. …”

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

“…Users seeking more generalized or policy-relevant distribution trends may find these averaged outputs preferable to projections from individual GCMs.…”

Supplementary Material for: Demographic Trends, Coalterations, and Imatinib Resistance across Genomic Variants in Gastrointestinal Stromal Tumors: An AACR Project GENIE Analysis by Stecko H. (19715551)

“…Introduction: Gastrointestinal stromal tumors (GIST) are the most common mesenchymal neoplasm of the gastrointestinal tract, the treatment of which represents a significant breakthrough in targeted cancer therapy. …”